We address the problem of finding multiple groups of words
or phrases that explain the underlying query facets, which
we refer to as query dimensions. We assume that the important
aspects of a query are usually presented and repeated in
the query’s top retrieved documents in the style of lists, and
query dimensions can be mined out by aggregating these significant
lists. Experimental results show that a large number
of lists do exist in the top results, and query dimensions generated
by grouping these lists are useful for users to learn
interesting knowledge about the queries.
|Published in||Proceedings of CIKM2011|
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